• Title/Summary/Keyword: 계층적 분류 방법

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The Importance Analysis of the Selection Factors for IPTV using AHP (계층적 분석방법을 활용한 IPTV 선택요인의 중요도 분석)

  • Ha, Gui-Ryong;Lee, Kyung-Tak
    • The Journal of the Korea Contents Association
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    • v.9 no.12
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    • pp.814-825
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    • 2009
  • This paper is to analyze the relative weight and the priority order of the selection factors for IPTV. To obtain the goal this paper, firstly, the selecting factors for IPTV were identified and conceptualized on reviewing previous literatures. And this paper proposed the hierarchy model using the factor analysis on IPTV users. and utilized AHP in analysis method. Secondly, AHP model constructed 4 higher factors, and 15 lower factors. The higher factors were 'Quality Acceptance', 'Social Effect', 'Using Motive' and 'Individual Psychology'. Results of this study show that relative weights among factors IPTV selection were founded as 'Quality Acceptance(33.0%)', 'Utilization Motive(31.8%)', 'Individual Psychology(21.3%)' and 'Social Influence(13.9%)'. Economic efficiency takes the top rank in sub-criteria included 15 factors and than convenience, amount of information, discrimination, self-efficacy, innovation, relative advantage in order listed. For the generalization of the research results, further researchs are needed to investigate intended use of IPTV on other method of analysis.

Pattern Clustering of Symmetric Regional Cerebral Edema on Brain MRI in Patients with Hepatic Encephalopathy (간성뇌증 환자의 뇌 자기공명영상에서 대칭적인 지역 뇌부종 양상의 군집화)

  • Chun Geun Lim;Hui Joong Lee
    • Journal of the Korean Society of Radiology
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    • v.85 no.2
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    • pp.381-393
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    • 2024
  • Purpose Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ2 distance measure and Ward's method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

Chungnam Symbol Representing Rural Landscape Elements and Compares the Importance Discussion of Using the AHP technique (AHP기법을 이용한 충남상징요소 및 농산어촌 대표경관 중요도 비교고찰)

  • Song, Byeong-Hwa;Kim, Hag-Hyun;Lee, Jung-Seob
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2011.10a
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    • pp.17-17
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    • 2011
  • 본 연구는 지역이 가지고 있는 중요한 자원을 자연 생태적 요소, 역사 문화적 요소, 시각 환경적 요소 등으로 분류한 후 충남지역 16개 시 군을 대상으로 군의 상징적 요소로서 가치 있는 자원의 발굴과 동시에 개발에 밀려 점점 사라져가는 농산어촌 대표경관의 추출을 통해 자원의 중요성을 AHP(계층 분석적 의사 결정기법)모델을 통해 분석하여 상호 중요도를 파악하고자 한다. 이러한 연구를 통해 지역의 대표적인 상징적 요소와 경관적 요소의 상관성을 파악함과 동시에 중요도에 따라 순위(ranking ordering)를 결정함으로서 지역의 정체성(identity)을 확보하고, 향후 보전할 자원의 특성을 파악함으로써 지역의 문화적, 환경적, 생태적 자원가치의 패러다임을 구축하고자 한다. 연구방법은 1차적으로 문헌조사를 통한 지역의 자원특성에 대한 분류체계를 설정한 후 전문가 집단을 선정하여 설문조사를 통한 통계적 분석방법을 사용하고자 한다. 전문가 집단은 지역에 대한 비교적 잘 파악하고 있는 지역전문가(관련대학 교수, 공무원, 연구원 등)로 구성하였으며, 1, 2차 설문을 통한 상징성 및 대표경관자원을 최종적으로 선정한 후, 3차 설문에서는 농촌 및 경관관련 전문가 집단을 재선정하여 AHP(계층 분석적 의사결정)기법을 통한 자원의 중요도를 파악하고자 한다. 분석방법은 자료의 계량적 분석을 위해 통계프로그램인 SPSS 12.0 for Windows와 도출된 상징요소의 가중치를 파악하기 위해 AHP 프로그램인 ExpertChoice 2006을 사용하여 도출된 상징요소의 가중치별 순위를 측정하여 분석의 과학성, 논리성, 타당성을 확보하고자 한다.

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A Study on the Performance Enhancement of Communication Mechanism for Distributed Intrusion Detection (분산 침입 탐지 통신 메커니즘의 성능 향상에 관한 연구)

  • 장정숙;전용희
    • Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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    • 2002.11a
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    • pp.16-19
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    • 2002
  • 분산 침입 탐지시스템은 감시되는 호스트 수에 비례하여 데이터 분석이 다수의 위치에서 수행되는 시스템이다. 따라서, 침입 탐지를 위하여 구성된 컴포넌트 사이의 효율적인 정보 분배가 중요한 문제이며, 통신 메커니즘은 신뢰성, 효율성, 안전성 그리고 확장성이 요구된다. 분산 침입 탐지 시스템의 통신 형태를 나타내는 통신모델 중에서, 높은 확장성 때문에 고려되고 있는 모델로 피어 대 피어 통신 모델이 있다. 이 모델은 특정한 형태의 관심전파와 데이터 전달 방법에 따라 다시 계층적 구조와 직접 연결로 분류할 수 있다. 본 논문에서는, 분산 침입탐지에서 침입 탐지정보를 전달하는 두 가지 방법에 대하여 분석하고, 통신 메커니즘의 성능을 향상시키는 방안을 제시하고자 한다.

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Multi Event Server Architecture for Hierarchical Event Service under Ubiquitous Network Environment (유비쿼터스 네트웍 환경에서 계층적 이벤트 서비스를 위한 다중 이벤트 서버 아키텍처)

  • 신준헌;박준호;강순주;최준용
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.4B
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    • pp.424-434
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    • 2004
  • Ubiquitous network consists of various devices using several heterogeneous protocols and requires seamless communication between devices. This paper proposes a new hierarchical event service and multiple event server architecture to implement the service under ubiquitous environment. The proposed event service classifies devices by logical and physical location to abstract the idiosyncrasy of used protocols, and reduces network load. Due to the design consideration, the proposed architecture removes transfer of duplicated event data effectively. As a result, we can guarantee the reliable event delivery. The prototype multiple event server architecture was implemented according to the proposed idea and evaluated its performance under a home network test bed.

Content Analysis of Learning Classifications of Foodservice and Culinary Majors (외식조리전공의 학문분류에 대한 내용분석)

  • Han, Kyung-Soo;Shin, Sun-Hwa
    • Culinary science and hospitality research
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    • v.16 no.2
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    • pp.367-381
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    • 2010
  • The principal objective of this study was to compare domestic and foreign learning(science) classification systems for foodservice and culinary majors, and to identify any problems with the domestic learning classification system. This study entailed a comparison of domestic and foreign versions of scientific systems addressing hospitality management. This study involved content analysis, which proved to be a useful method for comparing secondary data, and was used to evaluate the science classification systems of the Korea Research Foundation, Korea Science and Engineering Foundation(Korea), National Science Foundation, Oracle Corporation(America), Natural Science and Engineering Research Council(Canada) and the Australian Bureau Of STATISTICS(Australia). As a result, the Korean classification systems were identified as being based on a hierarchical stepwise system, whereas those of other countries were classified on the basis of nominal classifications. The initial research conducted in this study lays the groundwork for effective learning classifications for foodservice and culinary majors in the future.

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Recursive Fuzzy Partition of Pattern Space for Automatic Generation of Decision Rules (결정규칙의 자동생성을 위한 패턴공간의 재귀적 퍼지분할)

  • 김봉근;최형일
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.2
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    • pp.28-43
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    • 1995
  • This paper concerns with automatic generation of fuzzy rules which can be used for pattern classification. Feature space is recursively subdivided into hyperspheres, and each hypersphere is represented by its centroid and bounding distance. Fuzzy rules are then generated based on the constructed hyperspheres. The resulting fuzzy rules have very simple premise parts, and they can be organized into a hierarchical structure so that classification process can be implemented very rapidly. The experimented results show that the suggested method works very well compared to other methods.

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Hierarchical Hidden Markov Model for Finger Language Recognition (지화 인식을 위한 계층적 은닉 마코프 모델)

  • Kwon, Jae-Hong;Kim, Tae-Yong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.9
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    • pp.77-85
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    • 2015
  • The finger language is the part of the sign language, which is a language system that expresses vowels and consonants with hand gestures. Korean finger language has 31 gestures and each of them needs a lot of learning models for accurate recognition. If there exist mass learning models, it spends a lot of time to search. So a real-time awareness system concentrates on how to reduce search spaces. For solving these problems, this paper suggest a hierarchy HMM structure that reduces the exploration space effectively without decreasing recognition rate. The Korean finger language is divided into 3 categories according to the direction of a wrist, and a model can be searched within these categories. Pre-classification can discern a similar finger Korean language. And it makes a search space to be managed effectively. Therefore the proposed method can be applied on the real-time recognition system. Experimental results demonstrate that the proposed method can reduce the time about three times than general HMM recognition method.

Development of a nonstationary regional frequency analysis model (비정상성 지역빈도해석 모형 개발)

  • Jung, Min-Kyu;Moon, Jangwon;Kim, Yun-Sung;Park, Sungsu;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.433-433
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    • 2022
  • 수자원 관리를 위한 설계수문량의 산정은 수문자료의 통계적 특성을 고려한 빈도해석을 통해 이루어지며, 대상 관측지점에 대해 개별적으로 수행되는 지점빈도해석과 수문학적으로 동질하다고 판단되는 지점들의 자료를 동시에 고려하는 지역빈도해석으로 분류된다. 기후변화에 의한 미래 수문량의 변동성을 고려하기 위해 비정상성 빈도해석이 요구되나 짧은 기록을 갖는 수문자료로부터 정확한 변화 추세를 평가하기 어렵다. 이에 따라 지역빈도해석을 통해 자료를 확충함으로써 자료에 대한 신뢰성을 확보하고 지역 전체에 대해 대표성을 갖는 확률수문량을 산정하는 것이 합리적이다. 본 연구에서는 극치강수량의 지역빈도해석에서 비정상성을 고려하기 위해 단순선형회귀 모형을 통해 시간항에 대한 강수량의 경향성을 탐지하였다. 계층적 Bayesian 모형을 통해 Partial Pooling 기법을 적용함으로써 기존 L-모멘트 방법(complete pooling)에서 고려하지 못하는 개별지역의 강수 특성을 고려하였으며 불확실성을 정량화하였다. 한강 유역 18개 지점의 극치강수량에 대해 비정상성 평가 결과 대부분 지점에서 양의 기울기를 확인하였으며 미래 빈도별 확률강수량의 증가율을 제시한다.

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Classification of Terrestrial LiDAR Data Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 지상 라이다 자료의 분류)

  • Choi, Seung-Pil;Cho, Ji-Hyun;Kim, Yeol;Kim, Jun-Seong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.139-144
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    • 2011
  • This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.